New Learning Paradigms in Soft Computing

• Main Authors: Jain, Lakhmi C. (Author, http://id.loc.gov/vocabulary/relators/aut), Kacprzyk, Janusz (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2002.
• Edition: 1st ed. 2002.
• Series: Studies in Fuzziness and Soft Computing, 84
• Subjects: Artificial intelligence.; Computational intelligence.; Artificial Intelligence.; Computational Intelligence.
• Physical Description: XII, 464 p. online resource.
• ISBN: 9783790818031
• ISSN: 1434-9922 ;
• DOI: 10.1007/978-3-7908-1803-1

Learning is a key issue in the analysis and design of all kinds of intelligent systems. In recent time many new paradigms of automated (machine) learning have been proposed in the literature. Soft computing, that has proved to be an effective and efficient tool in so many areas of science and technology, seems to offer new qualities in the realm of machine learning too. The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets, and evolutionary computations.